‘Montreal might eat its young, but Montreal won’t break us down’: The co-production of place, space and independent music in Mile End, 1995–2015
Bibliographic record
Abstract
Abstract This article seeks to link the processes of gentrification in Montreal’s Mile End neighbourhood with its musical history over the past twenty years. A selective chronology of independent music from the neighbourhood is described, beginning with the early years of instrumental rock group Godspeed You Black Emperor! and concluding with the recent output of electronic music label Arbutus Records, via the commercial breakthrough of Arcade Fire’s Funeral album in 2004. Through a discussion of the ideas of Henri Lefebvre, Sharon Zukin and David Ley’s interpretation of the theories of Pierre Bourdieu, it is argued that the music produced in the neighbourhood can be seen as unified with its physical spaces in a number of ways under contemporary capitalism; in their parallel trajectories of progression and renewal and in the way they both construct and are constructed by notions of ‘place’. While it is argued that the dynamism of the music scene in Mile End has been intimately connected to broader processes of urban economic restructuring, the article also highlights the challenges an increasingly gentrified Mile End faces in maintaining its status as a fertile centre of cultural production.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Theoretical or conceptual | medium |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".